Abstract

Background Previous studies of differences in mental health between
urban and rural populations are inconsistent.

Aims To examine whether a high level of urbanisation is associated
with increased incidence rates of psychosis and depression, after adjustment
for age, marital status, education and immigrant status.

Method Follow-up study of the total Swedish population aged
25–64 years with respect to first hospital admission for psychosis or
depression. Level of urbanisation was defined by population density and
divided into quintiles.

Results With increasing levels of urbanisation the incidence rates
of psychosis and depression rose. In the full models, those living in the most
densely populated areas (quintile 5) had 68–77% more risk of developing
psychosis and12–20% more risk of developing depression than the
reference group (quintile 1).

Conclusions A high level of urbanisation is associated with
increased risk of psychosis and depression for both women and men.

Although urbanisation in Western countries has led to profound psychosocial
changes in people’s lives, previous research on the effect of
urbanisation on mental health has been inconsistent. For example, a few
studies in the Netherlands showed that urbanisation was associated with
psychotic disorders (
Marcelis et
al, 1998; van Os et al,
2001,
2002), and some studies from
the USA revealed higher urban than rural rates of depression
(
Blazer et al, 1987;
Neff & Husaini, 1987).
Other studies from the USA and the UK found no urban–rural difference in
mental health (
Romans-Clarkson et
al, 1990;
Robins &
Regier, 1991;
Kessler et
al, 1994;
Parikh et
al, 1996). We wished to shed new light on this inconsistency.
For this purpose we analysed the whole Swedish adult population aged
25–64 years in a longitudinal study of incidence rates of both psychosis
and depression. The aim of this study was to examine whether a high level of
urbanisation is associated with an increased risk of developing psychosis and
depression for both women and men, after adjustment for individual demographic
and socioeconomic characteristics.

METHOD

Study population and information sources

Our follow-up study investigated the entire Swedish population, in total
4.4 million women and men aged 25–64 years on 31 December 1996. The
individuals were followed from 1 January 1997 to 31 December 1999, until first
admission to hospital for treatment of psychosis or depression, death from any
cause, emigration from Sweden, or until the end of the study. A total of 35
727 individuals with previous hospital admissions for psychosis or depression
during 1992–1996 were excluded. Information on demographic and
socioeconomic characteristics was obtained from a national database holding
annual individual data for the whole Swedish adult population. Personal
identification numbers were used to link these data to the Swedish Hospital
Discharge Register at the National Board of Health and Welfare. All
individuals had been previously geocoded to their area of residence or
small-area market statistics (SAMS) level, which allowed us to include the
level of urbanisation in the study. The whole of Sweden is divided into 9667
SAMS areas. The average population in each SAMS area is approximately 2000
persons for Stockholm and 1000 persons for the rest of Sweden. A total of 135
719 individuals (3%) were excluded from the study because of missing SAMS
codes and/or other explanatory variables, or because they lived in SAMS areas
with fewer than 50 individuals; such areas were excluded from the study
because of unstable statistical estimates. The analysis eventually included
8135 SAMS areas.

Outcome variable

Psychiatric morbidity was defined as the first admission to hospital for
treatment of psychosis or depression defined according to ICD–9 and
ICD–10 (World Health Organization,
1978,
1992). There were two
diagnostic groups: psychosis (ICD–9 codes 295, 297, 298C, 298E, 298W,
298X; and ICD–10 codes F20–25, F28, F29) and depression
(ICD–9 codes 296, 298A, 298B, 300E, 301B, 311; ICD–10 codes
F30–34, F38, F39). The DSM–IV
(
American Psychiatric Association,
1994) was also used as an instrument in the process of
diagnosis.

Explanatory variables

The study population was categorised by gender, and by age into the
following groups: 25–34 years, 35–44 years, 45–54 years, and
55–64 years of age at the start of study. Level of urbanisation was
classified into quintiles by dividing all 4.4 million individuals into five
groups according to the population density in the SAMS area where they lived.
The population density was calculated as the number of people living in the
SAMS area divided by the area in km2. The quintiles were classified
as follows: quintile 1, ≤19; quintile 2, 20–273; quintile 3,
274–818; quintile 4, 819–2278; quintile 5, ≥2279 (all values in
persons per km2).

Marital status was classified in two categories: living alone, and
married/cohabiting. Only individuals with children in common registered at the
same property were counted as being cohabiting. Cohabiting without children in
common is registered in the national database as ‘single’, and
therefore in this study was counted as ‘living alone’.

Attained level of education was used as a measure of socio-economic status
and classified into three categories: ‘low’ (compulsory school), ‘
middle’ (at most 2 years of university study) and ‘
high’ (at least 3 years of university study).

Immigrant status was classified into three groups. The first group
consisted of people born in countries with mainly labour-related immigration
to Sweden (southern European countries and member states of the Organisation
for Economic Co-operation and Development); the second group consisted of
people born in countries often referred to as refugee countries (Eastern
European countries, Bosnia, and all other non-European countries); and the
third group consisted of Swedish-born people.

We performed separate analyses for women and men because of the gender
differences in psychiatric disease established in previous research. Moreover,
many psychiatric disorders decline with increasing age and socio-economic
status, which is why we included age and attained level of education in the
analysis (
Kessler et al,
1994). Marital status was included in the analysis because of its
relationship with, for example, depression
(
Carroll et al, 2003).
Finally, the importance of immigrant status for mental health was recently
confirmed by the Swedish National Institute of Public Health
(
Sundquist & Johansson,
2002) and by a longitudinal study of different migrant groups in
Sweden (
Westman et al,
2003).

During the follow-up 30% of the population had moved from one SAMS area to
another. Therefore, we added the variable moved/not moved in an additional
analysis (data not shown).

Statistical analysis

The SAS software package (version 6) was used in the statistical analyses
(
SAS, 1989). Age-standardised
incidence rates (per 100 000 persons per year) of psychosis and depression
were calculated by indirect age standardisation, with Sweden as the standard
population (
Breslow & Day,
1987). A Cox regression model
(
Kleinbaum, 1995) was used to
estimate the hazard ratios of psychosis and depression in the different
background variables. The results are shown as hazard ratios (HR) with 95%
confidence intervals. Risk time was calculated from the start of study until
the first admission to hospital because of psychosis or depression, death from
all causes, emigration from Sweden, or end of the study. The proportional
hazards assumption was tested for parallelism by studying log(–log(.))
of survival curves. All variables met the assumption; no interaction between
the explanatory variables and time was found.

The study was approved by the ethics committee at the Karolinska Institute,
Stockholm.

RESULTS

During the 3 years of the study there were 3133 and 3030 incident cases of
psychosis and 6357 and 4721 incident cases of depression in women and men
respectively.
Table 1 shows the
age-adjusted incidence rates of psychosis and depression for the five levels
of urbanisation and for the explanatory variables. There was a clear gradient
between level of urbanisation and incidence rates of psychosis and depression
for both women and men.
Table 2
shows the age-adjusted and full models for women. The age-adjusted model is
shown because psychiatric disorders decline with increasing age
(
Kessler et al,
1994). In the age-adjusted model there was a clear gradient
between level of urbanisation and the risk of developing both psychosis and
depression for women. For example, in quintile 5 (the highest level of
urbanisation), the risks of developing psychosis and depression were 166 and
43% higher than in quintile 1, respectively (psychosis, HR=2.66, 95% CI
2.36–2.99; depression, HR=1.43, 95% CI 1.32–1.55). The gradients
between level of urbanisation and the risk of developing psychosis and
depression remained in the full models, adjusted for marital status, attained
level of education, and immigrant status. For example, in quintile 5 the
hazard ratios for psychosis and depression for women were 1.77 (95% CI
1.57–1.99) and 1.20 (95% CI 1.11–1.30), respectively.

Risks of psychosis and depression in women aged 25-64 years
(n=2 189 190)

Table 3 shows the
age-adjusted and full models for men. The results show patterns similar to
those for women, with a clear gradient between level of urbanisation and risk
of developing psychosis or depression. For example, for men living in the most
urbanised areas, the risks of developing psychosis or depression were 125% and
27% higher than for those in the least urbanised areas. These increased risks
decreased slightly but remained significant after adjustment for marital
status, attained level of education and immigrant status. In the full model,
men living in the most urbanised areas (quintile 5), had 68% and 12% higher
risks of developing psychosis and depression, respectively, than men in the
least urbanised areas. When we added the variable ‘moved/not
moved’, the hazard ratios remained almost unaltered: for example, in the
full models the hazard ratios for psychosis in quintile 5 were 1.76 (95% CI
1.55–198) for women and 1.67 (95% CI 1.49–1.88) for men (data not
shown).

There was also a clear association between the covariates marital status,
attained level of education and immigrant status, and our outcome variables.
For example, in the full model the hazard ratio for psychosis in quintile 5
for people living alone was 6.02 (95% CI 6.45–6.64) for men and 3.23
(95% CI 2.98–3.49) for women. A similar pattern was observed for low
educational attainment. Individuals categorised as labour migrants or refugees
exhibited increased risks of developing psychosis and depression.

DISCUSSION

The main finding of this follow-up study was that a high level of
urbanisation was associated with increased incidence rates of psychosis and
depression for both women and men. This association remained after adjustment
for age, marital status, attained level of education and immigrant status, and
was more pronounced for psychosis than for depression. Moreover, the
covariates living alone and low educational attainment were strongly
associated with psychosis and depression, especially for men.

Other studies

Our findings of an association between urbanisation and depression were in
agreement with some studies from the USA
(
Blazer et al, 1987;
Neff & Husaini, 1987). A
few studies from the Netherlands revealed higher urban than rural rates of
psychosis (
Marcelis et al,
1998; van Os et al,
2001,
2002). One of these studies
confirmed that a high level of urbanisation was associated with psychotic
disorders, after adjustment for individual demographic and socio-economic
characteristics, findings in agreement with our study
(
van Os et al, 2002).
However, a study from the UK showed strong urban–rural differences in
mental health that did not remain after adjustment for individual
socioeconomic characteristics (
Paykel
et al, 2000). Other studies from the USA and the UK did
not agree with our study, finding no urban–rural difference in mental
health (
Romans-Clarkson et al,
1990;
Robins & Regier,
1991;
Kessler et al,
1994;
Parikh et al,
1996). In Canada, no difference was found for depression rates in
urban and rural Ontario (
Parikh et
al, 1996).

In summary, previous studies of possible urban–rural differences in
mental health are inconsistent. However, our findings of a significant
relationship between the level of urbanisation and psychiatric morbidity shed
new light on this inconsistency, because our study population consisted of the
entire adult population in Sweden, and we used incidence rates, rather than
prevalence rates, as our outcome.

Possible pathways

The pathways linking urbanisation and mental health have not yet been
clarified. For example, a British study based on data from 9777 individuals
showed urban–rural differences in psychiatric morbidity and substance
misuse, which were largely attributable to more adverse living circumstances
among individuals in urban social environments. These adverse circumstances
included stressful life events and low levels of social support
(
Paykel et al, 2000).
Social networks have been shown to be better in rural areas than in urban
areas for women (
Romans-Clarkson et
al, 1990). In addition, several previous studies have shown a
relationship between mood disorders, suicide attempts and poor social networks
(
Amann, 1991;
Johnsson Fridell et al,
1996;
Cheng et al,
2000;
Hirschfeld et
al, 2000); thus, poor social networks might be a mediator
between urbanisation and mental health. Another possible pathway linking
urbanisation and psychiatric disease is that an urban environment might
influence mental health in early life and increase general vulnerability to
schizophrenia later in life (
Marcelis
et al, 1999;
Pedersen & Mortensen, 2001). Some early risk factors associated with
schizophrenia are prenatal exposure to viral infections
(
Takei et al, 1995)
and poor nutrition (
Brown et al,
1995). Other possible pathways between urbanisation and
schizophrenia have also been discussed, such as daily life stress
(
van Os & McGuffin, 2003)
and chronic difficulties in urban areas
(
Brown & Prudo, 1981).

In The Netherlands it was found that about three-quarters of individuals
living in urban areas had also been born there
(
Marcelis et al,
1999). These findings indicate a relatively stable
urban–rural exposure over time, supporting the theory that being born
and/or spending one’s childhood in an urban environment increases the
risk of later developing a psychotic disorder. Some urban areas might also be
socio-economically deprived and ethnically segregated. However, these possible
pathways between urbanisation and mental health were not included in our
study. Finally, it is possible that there might be a biological synergism
between genetic liability and urban exposure. In a study from The Netherlands,
the authors found that both the level of urbanisation and familial liability
(defined as a family history of delusions and/or hallucinations necessitating
psychiatric treatment) increased the risk of psychotic disorder, independently
of each other. Moreover, the effect of urbanisation on the additive scale was
much larger for people with evidence of familial liability than for those
without familial liability (
van Os et
al, 2003).

Limitations and strengths

There are some limitations to this study. First, the database of the whole
Swedish adult population included only marital status as a measure of social
support. If rural areas have better social support than urban ones, it is
possible that people experiencing a first episode of psychosis or depression
are less likely to be admitted to hospital in rural areas. This might lead to
underestimates of the incidence of rural psychosis and depression owing to the
effects of community rather than institutional care. It is also possible that
the distribution of psychiatric beds across Sweden would bias our results if,
for example, the number of psychiatric beds was higher in urban areas;
however, we found that in the urbanised area of Stockholm County the number of
psychiatric beds was 0.52 per 1000 inhabitants, and in the rural northern
region it was 0.58 per 1000 inhabitants. The fact that cohabiting persons
without children in common are registered as living alone may result in
underestimates of the risks of psychiatric disease. Another limitation is that
we were not able to adjust our results for possible effects of selective
migration (e.g. from rural to urban areas), and the stress related to that
migration. However, after adjustment of our results for migration between SAMS
areas, the hazard ratios remained unaltered.

Our study also has a number of strengths. For example, the prospective
nature of our data allowed us to calculate incidence rates of psychosis and
depression, rather than prevalence rates. Data from the national database were
nearly complete for all variables. This completeness is made possible by the
Swedish registration system, which provides a personal identification number
for each individual. This number is used to link data from different
registers, and was used to follow each individual during the entire study
period.

Our urbanisation measure, calculated as population density, is an actual
measure of number of people per unit area. In another study of urbanisation
the population density was calculated as number of addresses per unit area
(
van Os et al, 2002),
which is not a precise measure of the actual number of people in that area.
The level of urbanisation was estimated in one study according to the
respondent’s own judgement, which implies a self-report bias
(
Paykel et al,
2000).

Our study population consisted of all Swedish women and men aged
25–64 years, in total 4.4 million persons. The validity of the diagnosis
from the Swedish In-Care Register has been shown to be high in an evaluation
by the Swedish National Board of Health and Social Welfare
(
National Board of Health and Welfare,
2000).

Implications

Our findings suggest that the level of urbanisation is associated with
psychosis and depression in both women and men. For clinicians in urban areas
who are involved in both treatment and prevention of disease, it is of great
importance to consider possible pathways in the development of psychiatric
morbidity. These pathways might include lack of social support, stressful life
events and familial liability. Moreover, when planning the distribution of
health care resources, it is important to consider the level of urbanisation
in order to improve services for people who are at high risk of developing
psychiatric morbidity.

Clinical Implications and Limitations

CLINICAL IMPLICATIONS

For clinicians in urban areas, it is important to consider the level of
urbanisation in the treatment and prevention of psychosis and depression.

This is even more important in the treatment of patients who are living
alone, have a low educational attainment and/or come from a foreign
country.

Decision-makers should consider the level of urbanisation when planning the
distribution of economic resources to psychiatric health care.

LIMITATIONS

There was a lack of data on social support. Rural hospital admissions may
not accurately reflect onset of psychiatric disorder if social support is
better in rural than in urban areas.

The fact that cohabiting people without children in common are registered
as living alone might lead to underestimates of the risks of psychiatric
disease.

We were not able to adjust our results for possible effects of selective
migration (e.g. from rural to urban areas) and the stress related to that
migration.

Acknowledgments

This work was supported by grants from the National Institutes of Health (I
R01 HL71084-01), the Swedish Council for Working Life and Social Research
(2001-2373), the Swedish Research Council (K2001-27X-11651-06C), the Knut and
Alice Wallenberg Foundation, and Stockholm County Council. The authors thank
Sanna Sundquist, student at Foothill College, California, for technical
assistance.

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